In underwater environments, acoustic signals are generated by a variety of acoustic sources, with examples including, but not limited to, marine mammals, fish, meteorological or geological phenomenon, as well as marine vehicles, such as military, recreational or commercial vehicles operating at or below the surface. Acoustic signals corresponding to a particular source can be particularly difficult to detect due to presence of noise in the marine environment. For example, acoustic data measured/recorded by a hydrophone can include significant noise (N) in addition to signals (S) associated with an acoustic source of interest, such that the data is actually represent a sum of the signal(s) and the noise (S+N). The noise components can be very significant, potentially masking many signals of interest. This problem of noise is often exacerbated by the typically anisotropic and temporally variable character of noise in undersea environments. See, e.g., Wenz, G., “Ambient Noise in the Ocean: Spectra and Sources,” J. Acoustic Soc. Am., Vol. 34, no. 12 (December 1962), the entire content of which is incorporated herein by reference.
Equipment for analyzing or characterizing acoustic signals in marine environments, e.g., in sub-surface conditions, have typically either been tethered or linked via underwater acoustic communications (ACOMMS) to an above-surface antenna, or have been included in under-water vessels that have large computing resources and power reserves, e.g., submarines. Generally, acoustic signal and target data in unmanned marine environments must be recorded, stored, transmitted and post-processed using a variety of complex disparate system components, such as sensors, transceivers, and computing devices before accurately detecting, classifying and tracking targets of interest. The ability to autonomously record, process and transmit marine acoustic signals associated with a target of interest in real-time has been limited by the processing power, battery life, available memory, communication capabilities, and/or the signal processing algorithms associated with a given vehicle platform or system implementation.